Uptake transporters belonging to the solute carrier (SLC) family are playing a pivotal role in the development of new drugs, mainly due to their involvement in drug-drug interactions, adverse drug effects and toxicity. Therefore, structure-based  modeling of SLC transporters can provide useful insights into binding events and resultant models can be applied for screening purposes. However, those efforts are limited by the lack of experimental 3D structure for the majority of SLC transporters, as well as their promiscuous nature with respect to ligand recognition.<br/>State-of-the-art docking protocols do not usually account for protein flexibility which is being recognized as one of the crucial aspects for target-ligand recognition. Last but not least, an automated workflow for transporter modeling is very handy if the modeling procedure has to be repeated in case of newly released crystal structures or new results from biochemical studies (e.g. mutational studies). Here, we present a (semi)automatic modeling pipeline which provides a promising strategy for structure-based molecular modeling including iterative design cycles. First, structural templates are detected on basis of fold-recognition methods. The initially detected template(s) is/are used to search the PDB database for analogous protein(s) with shared 3D fold. Afterwards, normal modes are calculated for identified proteins in order to explore their dynamics-based phylogeny, which can inform about possible additional templates suitable for homology modeling. Ensemble docking into multiple transporter conformations is then performed, since this presents a useful approach for unraveling binding mode hypotheses. For this purpose, an extensive conformational sampling of pre-selected templates is done on basis of normal modes. Distinct protein conformations are subsequently used for building structural comparative models of respective (SLC) transporter being captured in different functional states. Afterwards, large-scale docking screens into distinct structural models is performed to elucidate ligand binding events.<br/>Using the automatic workflow for generating binding mode hypotheses for a set of compounds with steroidal scaffold binding to three hepatic Organic Anion Transporting Polypeptides (OATP1B1, OATP1B3, and OATP2B1) delivered promising results which are currently under experimental evaluation. The protocol can be re-used for any target or off-target of pharmaceutical interest in the future.<br/>

Systematic pipeline for automated structure-based molecular design: Beyond the static picture of hepatic organic anion transporting polypeptides

2019 Fall National Meeting

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